SIMULATION OF TIMOTHY NUTRITIVE VALUE : A COMPARISON OF THREE PROCESS-BASED MODELS
Persson, T.1, Höglind, M.1, Van Oijen, M.2, Korhonen P.3, Palosuo, T.3, Jégo, G.4, Virkajärvi, P.3, Bélanger, G.4, Gustavsson, A.-M.5
1 Norwegian Institute of Bioeconomy Research (NIBIO), Særheim, Norway
2 Centre for Ecology and Hydrology, UK
3 Natural Resources Institute Finland (Luke), Helsinki, Finland
4 Agriculture and Agri-Food Canada (AAFC), Québec, Canada
5 Swedish University of Agricultural Sciences (SLU), Umeå, Sweden
BACKGROUND
– Timothy is a widely grown forage grass in cold temperate regions.
– Physiological characteristics and nutritive value vary between cultivars.
– Climate, weather, soil conditions, and mangement practices affect yield and quality
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BACKGROUND
– Process-based simulation models consist of equations, which represent the physiological processes behind sward growth and development and affect chemical composition.
– Different models respond differently to environmental and management factors, affecting the model prediction accuracy.
– Cultivar specific calibration improved the prediction of timothy yield with the models BASGRA, CATIMO and STICS (Korhonen et al
2018, Field Crops Research 224: 37-47).
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OBJECTIVES
– Compare the models BAGSRA, CATIMO and STICS as regards prediction accuracy of crude protein (CP) and fibre (NDF) concentration, and fibre digestibility (dNDF)
– Determine how cultivar-specific calibration affects the prediction accuracy of these attributes
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MODEL CHARACTERISTICS
– BASGRA, CATIMO and STICS:
– All models calculate growth by radiation use efficiency (RUE).
– All models simulate leave and stem fractions. BASGRA also simulates vegetative and generative tillers.
– All models calculate phenological development by growing degree days. In BASGRA day length also affects development.
– All models simulate nitrogen responses.
– STICS simulates soil water and nitrogen in multi-layers, while BASGRA and CATIMO simulate the soil in one single layer.
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MODEL CHARACTERISTICS
– In CATIMO and STICS, plant N requirements decrease with increasing shoot biomass. In BASGRA, plant N requirements are determined by the sward LAI and the extinction coefficient.
– The amount of cell walls (NDF)/the digestibility of cell walls (dNDF), increases/decreases with phenological stage in all three models.
– All models: Different rates of NDF change in stems and leaves
– CATIMO and STICS: NDF/dNDF also directly affected by temperature
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– Data on crude protein, NDF and dNDF from field trials in four countries
– six varieties
– a wide range of climate and soil conditions, and N fertilizer regimes
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SIMULATION SETTINGS
– Two types of calibration
1. Cultivar-specific calibration
2. Calibration of all cultivars together (generic calibration)
– Separate calibration and validation datasets.
– All simulations were initiated at the beginning of the growing season in the spring
– Calibrations techniques were allowed to differ between the models
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CRUDE PROTEIN
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calib
ration
valid
ation
BASGRA
Observ
ed C
rude P
rote
in (
g g
DM
-1)
0.0
0.1
0.2
0.3
CATIMO
BASGRA
0.0 0.1 0.2 0.3
0.0
0.1
0.2
0.3
CATIMO
Simulated Crude Protein (g g DM-1)
0.0 0.1 0.2 0.3
STICS
STICS
0.0 0.1 0.2 0.3
NEUTRAL DETERGENT FIBRE
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BASGRA
Simulated Neutral Detergent Fibres (g g-1 DM)
0.4 0.5 0.6 0.7
0.4
0.5
0.6
0.7
CATIMO
0.4 0.5 0.6 0.7
STICS
0.4 0.5 0.6 0.7 0.8
ca
libra
tio
n
Champ Nuutti GrindstadTammisto IIIki JonatanClimax1:1 line
va
lidatio
n
BASGRA
Obse
rve
d N
eu
tra
l D
ete
rgen
t F
ibre
s (
g g
-1 D
M)
0.4
0.5
0.6
0.7
0.8
CATIMO STICS
DIGESTIBILITY OF NDF
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BASGRA
Observ
ed d
igestibili
ty o
f N
eutr
al D
ete
rgent F
ibre
s (
g g
-1 N
DF
)
0.4
0.5
0.6
0.7
0.8
0.9
BASGRA
Simulated digestibility of Neutral Detergent Fibres (g g-1
NDF)
0.4 0.5 0.6 0.7 0.8
0.4
0.5
0.6
0.7
0.8
CATIMO
0.4 0.5 0.6 0.7 0.8
STICS val
0.4 0.5 0.6 0.7 0.8 0.9
STICS
STICS
calib
ration
valid
ation
CATIMO
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Number of
observations
Mean of
observation
Mean of
simulation
Normalised
RMSE (%)
rMBE
(%)
d-
index
Crude protein concentration (g g-1 DM)
BASGRA
173 0.14
0.15 16 -0.8 0.89
CATIMO 0.26 101 87 0.36
STICS 0.17 38 25 0.92
NDF concentration (g g-1 DM)
BASGRA
252 0.56
0.56 8.8 -0.4 0.72
CATIMO 0.55 17 -3 0.49
STICS 0.56 12 0.8 0.46
Digestibility of NDF g g-1 NDF)
BASGRA
28 0.78
0.75 9.3 -4 0.59
CATIMO 0.51 38 -34 0.34
STICS 0.79 6.4 0.23 0.82
CONCLUSIONS – NDF concentration and
dNDF predicted with similar accuracy as DM yield in previous studies
– Prediction of CP was poor compared with NDF and dNDF
– Cultivar-specific calibrations improved the performance of CATIMO and STICS, but not of BASGRA.
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